基于CT机器学习在尿石症中的研究进展

Research Progress of CT-Based Machine Learning in Urolithiasis

尿石症是泌尿系统最常见的疾病之一,CT是其术前诊断的首选检查方案。目前,机器学习(ML)被广泛应用于医学影像领域当中,基于ML的CT图像分析技术已经在尿石的自动分割、鉴别诊断、成分分析及术后疗效预测等方面表现出较好的效能。本文阐述CT图像的ML方法在尿石症中的研究进展,旨在指导和优化临床决策过程,以实现精准医疗。

Urolithiasis is one of the most common diseases of the urinary system,and CT is the first choice for its preoperative diagnosis.At present,machine learning(ML)is widely used in the field of medical imaging,and ML-based CT image analysis technology has shown good efficacy in automatic segmentation,differential diagnosis,component analysis and postoperative curative effect prediction of urolithiths.This paper describes the research progress of ML methods of CT images in urolithiasis,aiming to guide and optimize the clinical decision-making process to achieve precision medicine.